1. Datasets Used

1.1. ANES 2020 Time Series Study
Source: American National Election Studies (https://electionstudies.org/)
Included in Dataverse: No (publicly-available with licensing agreement). 

1.2 ANES 2019 Pilot
Source: American National Election Studies (https://electionstudies.org/)
Included in Dataverse: No (publicly-available with licensing agreement). 

1.3 CCES 2018
Source: Cooperative Congressional Election Study 2018 Common Content (https://cces.gov.harvard.edu/)
Included in Dataverse: No (publicly-available with licensing agreement). 

1.4 CCES 2018 - Munis 2020 Team Module
Source: Munis 2020. "Us over here versus them over there… literally: Measuring place resentment in American politics."
Included in Dataverse: Yes

1.5 2018/2019 Lucid
Source: Lunz Trujillo and Crowley 2022. "Symbolic versus material concerns of rural consciousness in the United States."
Included in Dataverse: No (contact Lunz Trujillo to request permission to access datasets). 


2. Replication Workflow

To fully reproduce the analyses, run the code in the following order. Be sure to have the above datasets downloaded into your working directory. 

2.1 Coding File for ANES2020

Stata .do script to create variables from raw 2020 American National Election Study (ANES) Time Series dataset.

2.2 Analysis File for ANES2020

Stata .do script for analyzing the 2020 American National Election Study (Coded). Includes both main text and supplemental analyses.

2.3 Out-of-Sample Replications

Stata .do script for coding and analyzing three out-of-sample replication datasets: 2018 CES (from Munis 2020), 2019 ANES (from Nelsen & Petsko 2021), and 2018/2019 Lucid (from Lunz Trujillo & Crowley 2022).


3. Notes on Reproducibility Limitations

Two components of the study cannot be made fully replicable due to data-access constraints:

3.1 Appendix 4L: Analysis using 2020 ANES Geocodes 

These analyses require restricted geographic identifiers. Users must individually apply to the ANES restricted data program via ICPSR to re-run these models. I include the model code and full Stata output logs to document the results.

3.2 Lunz Trujillo & Crowley (2022) Replication

Underlying reproduction materials were shared privately and cannot be redistributed. As with the ANES restricted analyses, I include both the code and full Stata output logs reproducing the results.


4. Contact

For questions about the data or replication materials, contact:
Trent Ollerenshaw
Assistant Professor, University of Houston
Email: tollerenshaw@uh.edu